As part of our work at prehype – we get to come advisors to various great entrepreneurs. One of these is Anthony from StreetSpark who with what seems to be everlasting energy keeps trying to find out how you can best match people.
He and the other great guys at Streetspark does this by looking at your digital trail and introduce you to people who have overlapping interests. It started out being very much centered about introductions to people who you could flirt with based on stated preferences. However, half way through development on StreetSpark we had a thought. There should be a system that looks across users’ sharing activity on social networks and works out who they should be introduced to based on what ‘shared things’ they have in common. It should show you what you both have in common right up front so you can decide if you want to meet them. Like a good host at a party.
There are people out there that hang out at the same types of places you do (and check in there), follow the same people on twitter, listen to the same music (Pandora, LastFM) and ‘like’ the same types of articles as you on blogs. They went to the same University and are in the same profession or maybe even worked for the same company (LinkedIn). And they’re sharing this stuff now as this stuff is what’s on their minds at the moment (people’s interests change all the time). All of this is recored and shared across social networks. So why not use this data that people have already shared for their own benefit?
If you were matched and introduced based on social network sharing data, it’s more likely that you’d have a good conversation with the people you’d meet. And it would open up the possibility of more serendipitous encounters – you’d see overlaps of not only interests but timings – things you’d both done around the same time. To do this used to require knowing someone who knows you both and then having them take the time to introduce you. Not any more. Your digital trail gives you away.
Turns out it takes a system that matches based on singular (1 to 1) connections and matches both sides to create a single matched ‘object’ rather than just a filtered search. This is the only way the reasons for the match (the common overlaps) can be shown up front. This is exactly the back-end system the guys at Streetspark had built. As so often happens, they just stumbled across a better use for our technology along the way.
The challenge now is to create the UX that will allow the existing user base to get full benefit from this more advanced matching – as well as allowing new users to use the app for getting introduced to like-minded people. What we are currently trying to figure out – is if we should build a separate app for users who are only interested in meeting like-minded people and leave the current app to their flirty colleagues. Thoughts are welcome? 🙂